Enterprise Distributed Application Service (EDAS) integrates with Application Real-Time Monitoring Service (ARMS) so that you can monitor key performance metrics and manage alerts for your applications that are deployed to EDAS.
Implement application monitoring
EDAS integrates with ARMS so that you can monitor key performance metrics for your applications that are deployed to EDAS. This helps you locate interfaces that have errors or slowly respond and make the called parameters reoccur. Therefore, the efficiency of problem diagnostics in the production environment is significantly improved.
|Application Overview||On the Application Overview page of an application, you can view the information about the related Kubernetes cluster, such as the region, microservice namespace, and status of the cluster, and the application diagnosis report. You can also view key metrics for the health status of the application. The metrics are classified into overall metrics, metrics of provided Services and dependent Services, and system metrics. Overall metrics include the total number of requests and average response time. System metrics include CPU utilization and memory usage.||View the overall information about an application|
|Prometheus||The preset monitoring dashboards that are provided by the Prometheus monitoring feature show the basic information, CPU metrics, memory metrics, and network metrics of pods. On these dashboards, you can view the Prometheus monitoring metrics, and change the properties of dashboard data as needed, such as time intervals and refresh rate.||View Prometheus monitoring metrics|
|Instance Details||EDAS provides various application monitoring metrics:
|Service Details||This feature is used to monitor the details of interface calls of an application, including SQL analysis, NoSQL analysis, exception analysis, error analysis, upstream and downstream services, and interface snapshots.||Service and API monitoring|
|Application Diagnosis - Real-time Diagnosis||This feature is applicable to scenarios in which you need to monitor application performance and identify the causes of problems in a short period of time.||Real-time diagnostics|
|Application Diagnosis - Exceptions Diagnosis||The application exception analysis feature collects statistics on the number of exceptions, the number of exceptions of each type, and the ports on which exceptions occur.||Exception analysis|
|Application Diagnosis - Threads Profiling||This feature provides statistics on the CPU time consumption at the thread level and the number of threads of each type. The method stacks of threads are recorded and aggregated every 5 minutes. This helps you review the code execution process and locate thread issues.||Thread profiling|
You can customize alert rules for specific monitored objects. If a rule is triggered, the system sends alert messages to the specified contact group by using the notification method that you specify. This way, the contacts can resolve issues at the earliest opportunity.